Bassem Ben Cheikh
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Oncology
- Molecular Biology
- Co-authors
- Daniel RacoceanuMichael PfeifferDavid SneadNasir RajpootHao ChenElia BruniBogdan J. MatuszewskiAnton Böhm
- Topics
- AI in cancer detection (6 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Single-cell and spatial transcriptomics (3 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsThe Journal of Immunology
- Partner nations
- FranceAustraliaUnited States
In The Last Decade
Bassem Ben Cheikh
17 papers receiving 768 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 443
- Computer Vision and Pattern Recognition 344
- Radiology, Nuclear Medicine and Imaging 299
- Oncology 157
- Molecular Biology 136
Countries citing papers authored by Bassem Ben Cheikh
This map shows the geographic impact of Bassem Ben Cheikh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bassem Ben Cheikh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bassem Ben Cheikh more than expected).
Fields of papers citing papers by Bassem Ben Cheikh
This network shows the impact of papers produced by Bassem Ben Cheikh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bassem Ben Cheikh. The network helps show where Bassem Ben Cheikh may publish in the future.
Co-authorship network of co-authors of Bassem Ben Cheikh
This figure shows the co-authorship network connecting the top 25 collaborators of Bassem Ben Cheikh. A scholar is included among the top collaborators of Bassem Ben Cheikh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bassem Ben Cheikh. Bassem Ben Cheikh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 20 | |
| 6 | 5 | |
| 7 | 103 | |
| 8 | 1 | |
| 9 | 42 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | Gland segmentation in colon histology images: The glas challenge contestbreakdown → | 570 |
| 14 | 4 | |
| 15 | 9 | |
| 16 | Preliminary approach for crypt detection in Inflammatory Bowel Disease | 1 |
| 17 | 1 | |
| 18 | 3 |
About Bassem Ben Cheikh
Bassem Ben Cheikh is a scholar working on Structural Biology, Biophysics and Surfaces, Coatings and Films, having authored 18 papers that have together received 778 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Single-cell and spatial transcriptomics (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (344 citations), Biophysics (80 citations) and Artificial Intelligence (443 citations). Bassem Ben Cheikh has collaborated with scholars based in France, Australia and United States. Frequent co-authors include Daniel Racoceanu, Michael Pfeiffer, David Snead, Nasir Rajpoot, Hao Chen, Elia Bruni, Bogdan J. Matuszewski, Anton Böhm, Xiaojuan Qi and Pheng‐Ann Heng. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Immunology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.